ai.libs.jaicore.ml.tsc.classifier.trees

Class LearnPatternSimilarityClassifier

java.lang.Object

ai.libs.jaicore.ml.tsc.classifier.ASimplifiedTSClassifier<java.lang.Integer>

ai.libs.jaicore.ml.tsc.classifier.trees.LearnPatternSimilarityClassifier

public class LearnPatternSimilarityClassifier
extends ASimplifiedTSClassifier<java.lang.Integer>

Class representing the Learn Pattern Similarity classifier as described in Baydogan, Mustafa & Runger, George. (2015). Time series representation and similarity based on local autopatterns. Data Mining and Knowledge Discovery. 30. 1-34. 10.1007/s10618-015-0425-y. This classifier currently only supports univariate time series prediction.

Field Summary

Fields inherited from class ai.libs.jaicore.ml.tsc.classifier.ASimplifiedTSClassifier

classMapper, trained

Constructor Summary

Constructors

Constructor and Description
LearnPatternSimilarityClassifier(int seed, int numTrees, int maxTreeDepth, int numSegments) Standard constructor.

Method Summary

Modifier and Type	Method and Description
int	findNearestInstanceIndex(int[][] leafNodeCounts) Performs a simple nearest neighbor search on the stored trainLeafNodes for the given leafNodeCounts using Manhattan distance.
java.util.List<weka.core.Attribute>	getAttributes()
int[]	getClassAttIndexPerTree()
LearnPatternSimilarityLearningAlgorithm	getLearningAlgorithm(TimeSeriesDataset dataset)
int[]	getLengthPerTree()
int[][]	getSegments()
int[][]	getSegmentsDifference()
int[][][]	getTrainLeafNodes()
int[]	getTrainTargets()
AccessibleRandomTree[]	getTrees()
java.lang.Integer	predict(double[] univInstance) Predicts the class by generated segment and segment difference features based on segments and segmentsDifference.
java.lang.Integer	predict(java.util.List<double[]> multivInstance) Performs a prediction based on the given multivariate list of double[] instance representation and returns the result.
java.util.List<java.lang.Integer>	predict(TimeSeriesDataset dataset) Performs predictions based on the given instances in the given dataset.
void	setAttributes(java.util.List<weka.core.Attribute> attributes)
void	setClassAttIndexPerTree(int[] classAttIndexPerTree)
void	setLengthPerTree(int[] lengthPerTree)
void	setSegments(int[][] segments)
void	setSegmentsDifference(int[][] segmentsDifference)
void	setTrainLeafNodes(int[][][] trainLeafNodes)
void	setTrainTargets(int[] trainTargets)
void	setTrees(AccessibleRandomTree[] trees)

Methods inherited from class ai.libs.jaicore.ml.tsc.classifier.ASimplifiedTSClassifier

getClassMapper, isTrained, setClassMapper, train

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

LearnPatternSimilarityClassifier

public LearnPatternSimilarityClassifier(int seed,
                                        int numTrees,
                                        int maxTreeDepth,
                                        int numSegments)

Standard constructor.

Parameters:

seed - Seed used for randomized operations

numTrees - Number of trees being trained

maxTreeDepth - Maximum depth of the trained trees

numSegments - Number of segments used per tree for feature generation

Method Detail

predict

public java.lang.Integer predict(double[] univInstance)
                          throws PredictionException

Predicts the class by generated segment and segment difference features based on segments and segmentsDifference. The induced instances are propagated to the forest of RandomRegressionTrees trees. The predicted leaf nodes are used within a 1NN search on the training leaf nodes to find the nearest instance and taking its class as prediction value.

Specified by:

predict in class ASimplifiedTSClassifier<java.lang.Integer>

Parameters:

univInstance - Univariate instance to be predicted

Returns:

Returns the result of the prediction

Throws:

PredictionException - If something fails during the prediction process.

findNearestInstanceIndex

public int findNearestInstanceIndex(int[][] leafNodeCounts)

Performs a simple nearest neighbor search on the stored trainLeafNodes for the given leafNodeCounts using Manhattan distance.

Parameters:

leafNodeCounts - Leaf node counts induced during the prediction phase

Returns:

Returns the index of the nearest neighbor instance

predict

public java.lang.Integer predict(java.util.List<double[]> multivInstance)
                          throws PredictionException

Performs a prediction based on the given multivariate list of double[] instance representation and returns the result.

Specified by:

predict in class ASimplifiedTSClassifier<java.lang.Integer>

Parameters:

multivInstance - Multivariate instance given by a list of multiple double[] time series used for the prediction

Returns:

Returns the result of the prediction

Throws:

PredictionException - If something fails during the prediction process.

predict

public java.util.List<java.lang.Integer> predict(TimeSeriesDataset dataset)
                                          throws PredictionException

Performs predictions based on the given instances in the given dataset.

Specified by:

predict in class ASimplifiedTSClassifier<java.lang.Integer>

Parameters:

dataset - The TimeSeriesDataset for which predictions should be made.

Returns:

Returns the result of the predictions

Throws:

PredictionException - If something fails during the prediction process

getSegments

public int[][] getSegments()

Returns:

the segments

setSegments

public void setSegments(int[][] segments)

Parameters:

segments - the segments to set

getSegmentsDifference

public int[][] getSegmentsDifference()

Returns:

the segmentsDifference

setSegmentsDifference

public void setSegmentsDifference(int[][] segmentsDifference)

Parameters:

segmentsDifference - the segmentsDifference to set

getLengthPerTree

public int[] getLengthPerTree()

Returns:

the lengthPerTree

setLengthPerTree

public void setLengthPerTree(int[] lengthPerTree)

Parameters:

lengthPerTree - the lengthPerTree to set

getClassAttIndexPerTree

public int[] getClassAttIndexPerTree()

Returns:

the classAttIndexPerTree

setClassAttIndexPerTree

public void setClassAttIndexPerTree(int[] classAttIndexPerTree)

Parameters:

classAttIndexPerTree - the classAttIndexPerTree to set

getTrees

public AccessibleRandomTree[] getTrees()

Returns:

the trees

setTrees

public void setTrees(AccessibleRandomTree[] trees)

Parameters:

trees - the trees to set

getTrainLeafNodes

public int[][][] getTrainLeafNodes()

Returns:

the trainLeafNodes

setTrainLeafNodes

public void setTrainLeafNodes(int[][][] trainLeafNodes)

Parameters:

trainLeafNodes - the trainLeafNodes to set

getTrainTargets

public int[] getTrainTargets()

Returns:

the trainTargets

setTrainTargets

public void setTrainTargets(int[] trainTargets)

Parameters:

trainTargets - the trainTargets to set

getAttributes

public java.util.List<weka.core.Attribute> getAttributes()

Returns:

the attributes

setAttributes

public void setAttributes(java.util.List<weka.core.Attribute> attributes)

Parameters:

attributes - the attributes to set

getLearningAlgorithm

public LearnPatternSimilarityLearningAlgorithm getLearningAlgorithm(TimeSeriesDataset dataset)

Specified by:

getLearningAlgorithm in class ASimplifiedTSClassifier<java.lang.Integer>